CN112559679A - Method, device, equipment and storage medium for detecting spreading force of new political law media - Google Patents
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Abstract
The invention discloses a method for detecting the spreading force of a new political law medium, which comprises the following steps: acquiring new media data of a government department to be detected; inputting the new media data into a pre-trained political news classification model to obtain new political media data; and calculating the transmission power of the new political media according to the new political media data. According to the method for detecting the new political medium transmission capacity, objective data such as manuscripts and audience behavior data issued by a plurality of new medium channels are collected, quantitative analysis is conducted on the new medium transmission capacity of government departments, and the real-time performance, the objectivity and the accuracy of detection results are greatly improved.
Description
Technical Field
The invention relates to the technical field of new media, in particular to a method, a device, equipment and a storage medium for detecting the spreading force of a political and legal new media.
Background
In recent years, with the rapid development of internet technology and 5G technology, various media propagation channels are emerging continuously, such as new media like wechat public numbers, microblogs, jitters, today's headlines, etc., compared with traditional media, the propagation of new media emphasizes the interaction with audiences, such as praise, comment, forwarding, etc.
In the current political field, the media publicity department for measurement and evaluation is mainly based on the measurement standards of the traditional media, such as the number of issued documents, the reading amount and the like, the data source of the traditional method is mainly reported by all departments, the real-time performance and the objectivity of the data have great problems, and no specific quantitative index exists aiming at the characteristic that the interactivity is more emphasized by the new media, so that the transmission capability index system of the traditional media cannot be used for measuring the transmission capability of the new media.
Disclosure of Invention
The embodiment of the disclosure provides a method, a device, equipment and a storage medium for detecting the spreading force of a new political law medium. The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview and is intended to neither identify key/critical elements nor delineate the scope of such embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
In a first aspect, an embodiment of the present disclosure provides a method for detecting a new political media dissemination ability, including:
acquiring new media data of a government department to be detected;
inputting new media data into a pre-trained political news classification model to obtain new political media data;
and calculating the transmission power of the new political media according to the new political media data.
In one embodiment, after acquiring new media data of a government department to be detected, the method further comprises:
performing word segmentation processing and vectorization processing on the text of the new media data to obtain vectorized text data;
and extracting key words in the vectorized text data by adopting a TF-IDF algorithm.
In one embodiment, before inputting new media data into the pre-trained political news classification model, the method further comprises:
acquiring a marked political domain news corpus;
performing word segmentation processing and vectorization processing on text data in a news corpus to obtain vectorized text data;
extracting keywords of the vectorized text data by adopting a TF-IDF algorithm;
and training a political news classification model according to the keywords.
In one embodiment, calculating the spreading power of the new political media according to the new political media data comprises the following steps:
and calculating the spreading power of the new political and legal media according to the number of publications, the reading number, the influence, the number of prawns, the number of fans, the number of comments and the number of political and legal correlations in the new media data.
In one embodiment, the political relevance number is obtained according to the number of articles of the political new media acquired by the political news classification model.
In one embodiment, calculating the influence comprises:
acquiring articles to be calculated in new political media data and all news articles collected in a preset time period;
calculating the similarity between the articles to be calculated and all collected news articles;
adding the news articles with the similarity larger than a preset threshold into a similar article list;
and obtaining the influence value according to the number of the articles in the similar article list.
In a second aspect, an embodiment of the present disclosure provides a device for detecting a spreading force of a new political law medium, including:
the acquisition module is used for acquiring new media data of a government department to be detected;
the classification module is used for inputting the new media data into a pre-trained political news classification model to obtain new media data of the politics;
and the calculation module is used for calculating the transmission power of the new political media according to the new political media data.
In a third aspect, the disclosed embodiment provides a device for detecting the spreading force of a new political media, which is characterized by comprising a processor and a memory storing program instructions, wherein the processor is configured to execute the method for detecting the spreading force of the new political media provided by the above embodiment when executing the program instructions.
In a fourth aspect, the disclosed embodiment provides a computer-readable medium, which is characterized by having computer-readable instructions stored thereon, where the computer-readable instructions are executable by a processor to implement the method for detecting the spreading power of a new political media provided by the above embodiment.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
according to the method for detecting the spreading force of the new political media, objective data such as manuscripts and audience behavior data issued by a plurality of new media channels are collected, data are analyzed quantitatively, the spreading force of the new media of government departments is detected, and the real-time property, the accuracy and the objectivity of detection results are greatly improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is a schematic flow diagram illustrating a method for political new media transmissibility detection according to an exemplary embodiment;
FIG. 2 is a schematic flow diagram illustrating a method of training a political news classification model in accordance with an exemplary embodiment;
FIG. 3 is a flowchart illustrating a method of operating a political news classification model according to an exemplary embodiment;
FIG. 4 is a flow diagram illustrating a method of impact force calculation in accordance with an exemplary embodiment;
fig. 5 is a schematic structural diagram illustrating a device for detecting a new political media dissemination ability according to an exemplary embodiment;
FIG. 6 is a schematic diagram illustrating a political new media transmissibility detection apparatus in accordance with an exemplary embodiment;
FIG. 7 is a schematic diagram illustrating a computer storage medium in accordance with an exemplary embodiment.
Detailed Description
So that the manner in which the features and elements of the disclosed embodiments can be understood in detail, a more particular description of the disclosed embodiments, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. In the following description of the technology, for purposes of explanation, numerous details are set forth in order to provide a thorough understanding of the disclosed embodiments. However, one or more embodiments may be practiced without these details. In other instances, well-known structures and devices may be shown in simplified form in order to simplify the drawing.
The method for detecting the spreading force of the new political media provided by the embodiment of the application will be described in detail with reference to fig. 1 to 4.
Referring to fig. 1, the method specifically includes the following steps.
S101, new media data of a government department to be detected are obtained.
In an exemplary scenario, a new media dissemination effort of a certain government department needs to be detected, and new media data that has been published by the department within a preset time period is first acquired. For example, new media data that the department has published within one month is acquired.
The new media data may include media data such as WeChat data, microblog data, tremble data, today's headline data, and the like.
S102, inputting the new media data into a pre-trained political news classification model to obtain new media data of the political law.
In a possible implementation manner, the acquired new media data may not be new media data related to the politics, so the acquired new media data is firstly input into a politics news classification model trained in advance to obtain new media data related to the politics field.
Specifically, word segmentation processing and vectorization processing are carried out on the text of the obtained new media data to obtain vectorized text data, the inverse document frequency of each word is calculated by adopting a TF-IDF algorithm, the key words in the vectorized text data are extracted according to the inverse document frequency, and the key words are input into a pre-trained political news classification model to obtain media data related to the political field.
Fig. 3 is a schematic flow chart of a method for operating a political news classification model according to an exemplary embodiment, and as shown in fig. 3, a trained political news classification model is loaded first, then text data is obtained, word segmentation and vectorization are performed on the text to obtain vectorized text data, a TF-IDF algorithm is used to extract keywords in the vectorized text data, the keywords are input into the classification model for classification, new media data related to the political field is obtained, and classification results are stored.
In one exemplary scenario, training the political news classification model is included before inputting new media data into the pre-trained political news classification model.
Specifically, a marked political field news corpus is obtained, in a possible implementation manner, relevant political corpus is captured from a new media platform such as WeChat public number, today's headline and the like by using a crawler technology, preprocessing operations such as format processing and duplicate removal are carried out to obtain 43774 articles, and the articles are marked manually to obtain a political 1875 article, a public security 6647 article, an inspection 8404 article, a court 8720 article, a judicial 8021 article, a political 7301 article and other 2806 articles.
Performing word segmentation processing and vectorization processing on text data in a news corpus to obtain vectorized text data, extracting keywords of the vectorized text data by adopting a TF-IDF algorithm, and training a political news classification model according to the keywords.
Fig. 2 is a schematic flow chart of a method for training a political news classification model according to an exemplary embodiment, and as shown in fig. 2, training text data, that is, a labeled political news corpus is obtained, then word segmentation and vectorization are performed on texts in the corpus, a TF-IDF algorithm is used to extract keywords of the vectorized text data, the political news classification model is trained according to the keywords, verification is performed by using a verification set, and if the classification model meets requirements, the training is stopped, and the trained classification model is stored.
According to this step, new media data related to the political field can be obtained.
S103, calculating the spreading power of the new political media according to the new political media data.
In order to adapt to the form characteristics of the new media, the embodiment of the disclosure calculates the spreading power of the new political media according to the number of releases, the number of read data, the influence, the number of prawns, the number of fans, the number of comments and the number of political relations in the new media data.
In one possible implementation, the new media data may include WeChat data, microblog data, tremble data, and today's top data.
The WeChat data comprises article release number, release times, average reading number, highest reading number, influence, average praise number, highest praise number and political relevant number. The microblog data comprise microblog release number, original microblog number, bean vermicelli number, forwarding number, comment number, average praise number and highest praise number. The jittering data comprises release number, fan number, comment number, share number, average praise number and highest praise number. The current data comprises publication number, vermicelli number, reading number, comment number, average praise number, highest praise number and political correlation number.
Generally, users publish articles in WeChat and today, and political relevance numbers are set up in order to obtain the number of published articles related to the political field. In one possible implementation, the number of articles related to the political field obtained according to the political news classification model is the political relevance number.
For example, the police department may obtain the documents related to the police according to the classification model, the auditorium may obtain the documents related to the auditorium according to the classification model, and the court may obtain the documents related to the court.
Generally, there is no forward load of the micro-letter articles and the headpiece articles, and some articles have no marked source, and the forward load of a certain article needs to be calculated in order to know the influence of the article issued by the government department.
Fig. 4 is a schematic diagram of calculating influence of an article, and as shown in fig. 4, calculating influence of an article includes: the method comprises the steps of obtaining articles to be calculated in political new media data and all news articles collected in a preset time period, preprocessing the obtained articles, including utilizing a natural language processing technology to perform word segmentation on the obtained articles, performing feature word extraction to form feature parameters of texts, then calculating the similarity between the articles to be calculated and all collected news articles on a network, adding the network news articles with the similarity larger than a preset threshold value into a similar article list, and obtaining an influence value according to the number of the articles in the similar article list. According to the step, the articles similar to the articles sent by the government department and flowing on the network can be obtained, and further the forwarding amount of the articles sent by the government department, namely the influence of the articles sent by the government department, can be obtained.
Further, according to the new media data of the politics law, the spreading force of the new media is calculated. In a possible implementation manner, the wechat spreading capacity, the microblog spreading capacity, the tremble spreading capacity and the today's headline spreading capacity are respectively calculated, and the spreading capacity of the political new media is calculated according to the preset weights of the wechat spreading capacity, the microblog spreading capacity, the tremble spreading capacity and the today's headline spreading capacity.
In particular, the WeChat propagation force N1The calculation of (c) is as follows:
wherein N ismaxMaximum number of published articles, N, representing all departments within a statistical range111F, representing the number of articles released in the current department to be detectedmaxMaximum value of number of releases, N, of all departments within a statistical range112Indicating number of releases of current department to be detectedThe number of the first and second groups is,
maximum value of average reading number of all departments in statistical range, N121Indicating the average reading number of the current department to be detected, RmaxMaximum value of highest read number, N, for all departments within the statistical range122Indicating the highest reading number of the current department to be examined, ImaxMaximum value of influence, N, representing all departments within a statistical range123Indicating the influence of the currently examined department,
maximum value of average praise number of all departments in statistical range, N131Represents the average number of praise, Z, of the current department to be detectedmaxMaximum value of maximum like number of all departments in the statistical range, N132Representing the highest praise number, C, of the current department to be detectedmaxMaximum value of the political news related number, N, representing all departments within the statistical range141And showing the political relevant number of the current department to be detected.
Wherein, the selection of the weight meets the standardized condition:
microblog propagation force N2The calculation of (c) is as follows:
Nmaxmaximum number of published articles, N, representing all departments within a statistical range211Number of articles released from current department to be inspected, YmaxThe maximum value N of the number of original microblogs released by all departments in the statistical range is represented212Representing the number of original microblogs of the current department to be detected, BmaxRepresenting fans of all departments within a statistical rangeMaximum value, N221Number of fans indicating current department to be examined, ImaxMaximum value of the number of retransmissions representing all departments within the statistical range, N222Indicating the number of forwardings, P, of the current department to be examinedmaxMaximum number of comments, N, representing all departments within a statistical range223The number of comments of the department currently to be detected,
maximum value of average praise number of all departments in statistical range, N231Represents the average number of praise, Z, of the current department to be detectedmaxMaximum value of maximum like number of all departments in the statistical range, N232And representing the highest praise number of the current department to be detected.
Wherein, the selection of the weight meets the standardized condition:
tremble sound transmission force N3The calculation of (c) is as follows:
wherein N ismaxMaximum number of published articles, N, representing all departments within a statistical range311Indicating the number of publications currently in the department to be examined, BmaxMaximum number of fans representing all departments within the statistical range, N321Number of fans, P, representing current department to be examinedmaxMaximum number of comments, N, representing all departments within a statistical range322Number of comments indicating current department to be examined, ImaxMaximum value of the number of retransmissions representing all departments within the statistical range, N323Indicating the forwarding number of the department currently to be detected,
means average of all departments within the statistical rangeMaximum value of the number of praise, N331Represents the average number of praise, Z, of the current department to be detectedmaxMaximum value of maximum like number of all departments in the statistical range, N332And representing the highest praise number of the current department to be detected.
Wherein, the selection of the weight meets the standardized condition:
today's first item transmission force N4The calculation of (c) is as follows:
wherein N ismaxMaximum number of published articles, N, representing all departments within a statistical range411Number of articles released from current department to be inspected, BmaxMaximum number of fans representing all departments within the statistical range, N421Indicating the number of fans currently in the department to be detected, RmaxMaximum value of reading number of all departments in statistical range, N422Indicating the number of readings, P, of the current department to be examinedmaxMaximum number of comments, N, representing all departments within a statistical range423The number of comments of the department currently to be detected,
maximum value of average praise number of all departments in statistical range, N431Represents the average number of praise, Z, of the current department to be detectedmaxMaximum value of maximum like number of all departments in the statistical range, N432Representing the highest praise number, C, of the current department to be detectedmaxMaximum value of political correlation number, N, representing all departments within a statistical range441And showing the political relevant number of the current department to be detected.
Wherein, the selection of the weight meets the standardized condition:
after obtaining the WeChat spreading power, the microblog spreading power, the tremble spreading power and the today's first spreading power, calculating the new media data spreading power NCI of the government department according to the preset weight:
NCI＝w1*N1+w2*N2+w3*N3+w4*N4
also, the weights satisfy the normalization condition:
the weights of the propagation channels may be set by a person skilled in the art, and the embodiment of the present disclosure is not particularly limited. According to this step, the new media transmission power of the government department to be detected can be calculated. If the new media transmission power of a plurality of departments needs to be sequenced, the new media transmission power of each department can be respectively calculated according to the method.
According to the method for detecting the spreading power of the new political media, provided by the embodiment of the disclosure, objective data such as manuscripts and audience behavior data issued by a plurality of new media channels are collected, the spreading power of the new media of a government department is detected, and the real-time performance, the accuracy and the objectivity of a detection result are greatly improved.
The embodiment of the present disclosure further provides a device for detecting the propagation power of the new political media, where the device is configured to execute the method for detecting the propagation power of the new political media according to the foregoing embodiment, as shown in fig. 5, the device includes:
an obtaining module 501, configured to obtain new media data of a government department to be detected;
the classification module 502 is used for inputting new media data into a pre-trained political news classification model to obtain new political media data;
and the calculating module 503 is configured to calculate the spreading power of the new political media according to the new political media data.
It should be noted that, when the detection apparatus for the new political media transmission capability provided in the foregoing embodiment executes the detection method for the new political media transmission capability, the division of the functional modules is merely exemplified, and in practical applications, the function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules, so as to complete all or part of the functions described above. In addition, the device for detecting the propagation power of the new political media and the method for detecting the propagation power of the new political media provided by the embodiments belong to the same concept, and details of the implementation process are shown in the method embodiments and are not described herein.
In a third aspect, an embodiment of the present disclosure further provides an electronic device corresponding to the method for detecting the new political affairs media spreading force provided in the foregoing embodiment, so as to execute the method for detecting the new political affairs media spreading force.
Please refer to fig. 6, which illustrates a schematic diagram of an electronic device according to some embodiments of the present application. As shown in fig. 6, the electronic apparatus includes: the processor 600, the memory 601, the bus 602 and the communication interface 603, wherein the processor 600, the communication interface 603 and the memory 601 are connected through the bus 602; the memory 601 stores a computer program that can be executed on the processor 600, and the processor 600 executes the method for detecting the new political affairs media transmission capability provided by any one of the foregoing embodiments of the present application when executing the computer program.
The Memory 601 may include a high-speed Random Access Memory (RAM) and may further include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 603 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, and the like can be used.
The electronic device provided by the embodiment of the application and the method for detecting the propagation force of the new political and legal media provided by the embodiment of the application have the same beneficial effects as the method adopted, operated or realized by the electronic device.
In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium corresponding to the method for detecting the spreading force of the new political affairs medium provided in the foregoing embodiment, please refer to fig. 7, which illustrates a computer-readable storage medium, which is an optical disc 700, on which a computer program (i.e., a program product) is stored, and when the computer program is executed by a processor, the computer program performs the method for detecting the spreading force of the new political affairs medium provided in any of the foregoing embodiments.
It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory, or other optical and magnetic storage media, which are not described in detail herein.
The computer-readable storage medium provided by the above embodiment of the present application and the method for detecting the spreading force of the political novelty media provided by the embodiment of the present application have the same beneficial effects as the method adopted, operated or implemented by the application program stored in the computer-readable storage medium.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A method for detecting the spreading force of new political media is characterized by comprising the following steps:
acquiring new media data of a government department to be detected;
inputting the new media data into a pre-trained political news classification model to obtain new political media data;
and calculating the transmission power of the new political media according to the new political media data.
2. The method of claim 1, wherein after acquiring new media data of the government department to be detected, further comprising:
performing word segmentation processing and vectorization processing on the text of the new media data to obtain vectorized text data;
and extracting key words in the vectorized text data by adopting a TF-IDF algorithm.
3. The method of claim 1, wherein prior to entering the new media data into a pre-trained political news classification model, further comprising:
acquiring a marked political domain news corpus;
performing word segmentation processing and vectorization processing on the text data in the news corpus to obtain vectorized text data;
extracting key words of the vectorized text data by adopting a TF-IDF algorithm;
and training the political news classification model according to the keywords.
4. The method according to claim 1, wherein calculating the transmissibility of the political new media based on the political new media data comprises:
and calculating the spreading power of the new political and legal media according to the number of publications, the number of reading, the influence, the number of praise, the number of fan, the number of comments and the number of political and legal correlations in the new media data.
5. The method of claim 4, wherein the political relevance numbers are obtained from the number of articles of political new media obtained from a political news taxonomy model.
6. The method of claim 4, wherein calculating the influence comprises:
acquiring articles to be calculated in the new political media data and all news articles collected in a preset time period;
calculating the similarity between the article to be calculated and all collected news articles;
adding the news articles with the similarity larger than a preset threshold into a similar article list;
and obtaining the influence value according to the quantity of the articles in the similar article list.
7. A detection device for political new media transmission force is characterized by comprising:
the acquisition module is used for acquiring new media data of a government department to be detected;
the classification module is used for inputting the new media data into a pre-trained political news classification model to obtain political new media data;
and the calculation module is used for calculating the transmission power of the new political media according to the new political media data.
8. The apparatus of claim 7, further comprising:
the preprocessing module is used for performing word segmentation processing and vectorization processing on the text of the new media data to obtain vectorized text data;
and extracting key words in the vectorized text data by adopting a TF-IDF algorithm.
9. A device for detecting the spreading force of a new political medium, comprising a processor and a memory storing program instructions, wherein the processor is configured to execute the method for detecting the spreading force of a new political medium according to any one of claims 1 to 6 when executing the program instructions.
10. A computer readable medium having computer readable instructions stored thereon which are executable by a processor to implement a method of detecting the transmissibility of a political new medium according to any one of claims 1 to 6.
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